NASA Technical Reports Server (NTRS) 20020020997: On Precipitation Modification by Major Urban Areas: A New Perspective from TRMM

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by  NASA Technical Reports Server (NTRS)

P1.31 On Precipitation Modification by Major Urban Areas: A New Perspective
from TRMM
J. Marshall Shepherd
NASA-GSFC, Laboratory for Atmospheres, Greenbelt, Maryland
Harold Pierce
Science Systems and Applications, Inc. Lanham, Maryland
1. INTRODUCTION
Early investigations (Changnon 1968;
By year 2025, 80% of the world's population Landsberg 1970; Huff and Changnon 1972a and
will live in cities according to a 1999 United 1972b; Huff and Changnon 1973) found evidence
Nation's report. As cities continue to grow, urban of warm seasonal rainfall increases of 9 to 17%
sprawl creates unique challenges related to land over and downwind of major urban cities. The
use planning, transportation, agriculture, housing, Metropolitan Meteorological Experiment
pollution, and development. Urban expansion (METROMEX) was an extensive study that took
also has measurable impact on environmental place in the1970s in the United States (Changnon
process. et al. 1977; Huff 1986) to further investigate
modification of mesoscale and convective rainfall
Urban areas modify boundary layer by major cities. In general, results from
processes through the creation of "urban heat METROMEX have shown that urban effects lead
islands" or UHI. In cities, natural land surfaces to increased precipitation during the summer
are replaced by artificial surfaces that have very months. Increased precipitation was typically
different thermal properties (e.g. heat capacity, observed within and 50-75 km downwind of the
specific heat, and thermal inertia). Such surfaces city reflecting increases of 5%-25% over
are typically more capable of storing solar energy background values (Sanderson and Gorski 1978;
and converting it to sensible heat. As sensible Huff and Vogel 1978; Braham and Dungey 1978;
heat is transferred to the air, the temperature of Changnon 1979; Changnon et al. 1981; Chancjnon
the urban air tends to be 2-10 degrees higher et al. 1991). Using a numerical model, Hjemfelt
than surrounding non-urban areas (fig, 1). (1982) simulated the urban heat island of St.
Louis and found positive vertical velocities
downwind of the city. He suggested that the
SketcohfanUrbaHneat-[slaPnrdofile
enhanced surface roughness convergence effect
and the downwind shifting or enhancement of the
92o .............. UHI circulation by the synoptic flow were the
cause (fig. 2). METROMEX results also
suggested that areal extent and magnitude of
urban and downwind precipitation anomalies were
related to size of the urban area (Changnon
1992).
oo_ ...!............................._..............
Rural SuburbanCommercaalDowntownUrban Park Suburban Rural
Re_iden6al Residenbal Re_i_'en_aFlarmland
Fig.l-Typical Urban Heat Island Temperature
Profile
In the past 30 years, several observational
and climatological studies have theorized that the
UHI can have a significant influence on
mesoscale circulations and resulting convection.
* Corresponding author address: J. Marshall
Shepherd, NASA-GSFC, Code 912.0, Greenbelt,
MD 20771; [email protected] Fig.2-Mesoscale Circulation Induced by UHI.
website contains plots, figures, and graphs with
2. MOTIVATION and OBJECTIVES more specifics on the study.]
More recent studies have continued to
validate and extend the findings from pre- and
post-METROMEX investigations. Bailing and
Brazel (1987) observed more frequent late
afternoon storms in Phoenix during recent years
of explosive population growth. Analysis by
Bornstein and LeRoy (1990) found that New York
City effects both summer daytime thunderstorm
formation and movement. Jauregui and Romales
(1996) observed that the daytime heat island
seemed to be correlated with intensification of
rainshowers during the wet season (May-October)
in Mexico City. Selover (1997) found similar
results for moving summer convective storms
over Phoenix, Arizona. Bornstein and Lin (2000)
examined data from an Atlanta meso-network to
show that the UHI induced a convergence zone
that initiated storms during the summer of 1999.
Thielen et al. (2000) used a meso-gamma scale
model to address the extent of influence of urban Fig. 3-TRMM Spacecraft and Scan Strategy
surfaces on the development of convective
precipitation. The results showed that sensible 3. CONCLUSIONS and FUTURE WORK
heat fluxes and enhanced roughness due to the
urban heat island can have considerable influence The primary goal of part I of this study was to
on convective rainfall. establish that a 3-year, warm season climatology
of mean rainfall rates from the TRMM PR could be
The literature indicates that the signature of used to identify urban-induced rainfall anomalies.
the "urban heat island effect" may be resolvable The study provides one of the first (possibly the
in rainfall patterns over and downwind of first) published accounts of rainfall modification
metropolitan areas. However, a recent U.S. by urban cities that uses rainfall data from a
Weather Research Program panel concluded that satellite. It also illustrates a unique application of
more observational and modeling research is data from the first space-borne rain radar.
needed in this area (Dabberdt et al 2000).
Prevailing wind was determined based on a
Objectives: Employ Tropical Rainfall 19-year climatology of geopotential heights, the
Measuring Mission (TRMM) Precipitation Radar results validated previous ground-based and
data: modeling studies that identified urban-induced
rainfall maxima over and downwind of cities.
a.To validate and extend ground-based Using a 15-month climatology of mean rainfall
observations of climatological rainfall patterns rates at 2.0 km altitude, we examined the cities of
in major urban areas using satellite rain Atlanta, Montgomery, Dallas, Waco, and San
estimates. Antonio. We found that the average percentage
increase in mean rainfall rate in the hypothesized
b.To quantify the impact of urban areas on "downwind maximum area" over the "upwind
rainfall in and downwind of cities using satellite control area" was 28.4% with a range of 14.6%-
rain estimates. 51%. Over the urban area, the average change
was smaller (+5.8%) but exhibited a range of
c.To demonstrate the unique capabilities and -27.7%-24.7%. There was a slight indication that
opportunities to observe multiple urban rainfall regions orthogonal and to the right of the mean
climatologies over an extensive area (38 prevailing flow (within 50 km) experienced
degrees North to 38 degrees South) using the relatively significant increases in rainfall (10.7%).
TRMM PR data. However, the downwind region exhibited the most
significant changes. Tabes 1 and 2 summarize
d.To validate an unanticipated application of key results. More extensive results can be found
TRMM PR data to urban-environmental issues. at the previously mentioned website.
We also demonstrated that the maximum
[Note: The results discussed in this section rainfall rates found in the maximum impact area
can be found on the website that accompanies could exceed the mean value in the upwind
this extended abstract proceeding control area by 48-116%. This maximum value
(http:/trsd.qsfc.nasa.gov/912/urban). This was found at an average distance of 39 km from
the edge of the urban center or 64 km from the experimental and real-time weather prediction
exact center. The range was 20-60 km downwind models continue to approach smaller spatial
of the edge of the urban center. In general, the scales, this research may require mesoscale
changes in rainfall and their location relative to models to consider urban surfaces and their
the "non-urban" effect regions are extremely characteristics in surface/land parameterizations.
consistent with previous work related to This is particularly critical as urban growth
METROMEX and other studies. This fact continues to infringe upon green space at
provides confidence that UHI-rainfall effects are alarming rates. Additionally, the research has
real and satellite rainfall estimates from TRMM implications for policymakers, urban planners,
can detect them. water resource managers, and agriculture
professionals who may use an understanding of
Future work will be published as a separate urban rainfall climatology in the design of better
paper. Part II of the study will seek to establish drainage systems, planning of land-use, or
a robust validation of TRMM rainfall estimates identification of optimal areas for agricultural
using special rain gauge networks around the key activity. Additionally, the study further
cities in the study. We are atso interested in demonstrates the impact of human development
TRMM lightning data as an additional validation on environmental processes.
source. Additionally, we will seek to address the
physical mechanisms that lead to the observed
"city" and downwind maxima around cities during References available upon request.
the warm season. We will use a cloud-mesoscale
model to identify the role that the UHI plays in
enhancing or creating mesoscale circulations. We
will also seek to differentiate whether dynamic
forcing related to the mesoscale circulation (e.g.
destabilizing the boundary layer, enhanced
vertical motion), surface convergence due to
urban roughness, or a combination of both impact
warm season rainfall development. We will also
propose to develop a new urban land
parameterization for the cloud-mesoscale models
under study at NASA-Goddard.
The implications of the research presented
herein is broad. The estabtishment of TRMM's
ability to identify rainfall anomalies associated
with urban areas provides a powerful tool to
investigate urban effects due to cities around the
world, particularly in areas with sparse ground-
based rain measurement systems. The future
space-based rainfall measuring missions (e.g.
Global Precipitation Measurement) will extend
TRMM-like measurements to the mid-latitudes
thereby extending our approach to numerous
major cities not located in sub-tropical and
tropical latitudes that TRMM observed. As
City Mean Mean Mean Rainrate Percentage Change Percenta
Rainrate in Rainrate in over Urban in Maximum Change
Maximum Upwind Center Impact Area from Urban
Impact Area Control Area (mm/hr) Upwind Control Center A
(mm/hr) (mm/hr) Area from
Upwind
Control
Atlanta, 4.23 3.54 3.81 19.5 % 7.8 %
Georgia
Montgomery, 4.39 3.83 4.39 14.6% 9.9%
Alabama
Dallas, 4.00 3.03 3.78 32.0% 24.7%
Texas
Waco, 3.33 2.17 2.49 51.1% 14.7%
Texas
San Antoniol 3.29 2.63 1.90 25.0% -27.7%
Texas
Mean Percentage Change in Maximum Impact Area=28.4%
Mean Percentage Change in Urban Center=5.8%
Mean Percentage Change in Northern Minimum Impact Area=l.1%
Mean Percentage Change in Southern Minimum Impact Area=10.7%
Table 1.0-Mean rainrates (mm/hr) from TRMM Precipitation Radar data (2.0 km height).
The data is averaged over the specified upwind, downwind, and urban area for the warm
season (May-September) for 1998-2000. The percentage change from the upwind control
area is given for the "maximum impact" and urban center areas. Mean percentage change
for each area is also shown for all cities in the study.
City Maximum Rainrate Percentage Change in Distance Downwind
Value in Maximum Maximun Value in of Maximum
Impact Area (mm/hr) Maximum Impact Area Rainrate Value from
from Upwind Control Area Urban Center Area
Atlanta, 5.86 65.0% -60 km
Georgia
Montgomery, 5.69 48.5% -25 km
Alabama
Dallas, 4.52 49.1% -20 krn
Texas
Waco, 4.74 116.0% -50 km
Texas
San Antonio, 5.45 107.0% -40 km
Texas
Maximum rainrate value is found in the maximum impact area at a mean distances of -39 km from the
edge of the urban center (or -64 km from the exact center).
Table 2.0-Maximum 3-year warm season rainrate (mm/hr) found in the maximum impact
area. The table provides information on the distance and direction from the urban center to
the value in column 1.